The SRES scenarios span a wide range of future economic growth rates (Table
4-5) and resultant levels of economic output. The A1 scenario family, with a
global GDP of US$520 to 550 trillion in 2100, delineates the SRES upper bound,
whereas the A2 and B2 scenarios, with a range of US$230 to 250 trillion in 2100,
represent its lower bound. The B1 scenario family is intermediary. Although
the SRES scenarios span a wide range, both lower and higher global GDP levels
can be found in the literature (see Chapter 2).

Uncertainties in future GDP levels are governed by the rates of future productivity
growth and population growth, especially those in developing countries. Different
assumptions on conditions and possibilities for development "catch-up" and for
narrower per capita income gaps in particular explain the wide range in projected
future economic growth rates. Given the weak inverse relationship between population
growth and per capita income growth discussed in Chapter 2,
uncertainties in future population growth rates tend to restrict the range of
associated GDP projections. High population growth, all else being equal, lowers
per capita income growth, whereas low population growth tends to increase this
growth. This relationship is evident in empiric data - high per capita income
countries are generally also those that have completed their demographic transition.
The affluent live long and generally have few children. Notable exceptions are
countries with small populations and significant income from commodity exports.
Yet even assuming this relationship holds for an extended time into the future,
its quantification is subject to considerable theoretic and empiric uncertainties
(Alcamo et al., 1995).

As outlined above, two of the SRES scenarios explicitly explore alternative
pathways of the gradually closure of existing income gaps. As a reflection of
uncertainty, the development "catch-up" diverges in terms of geographically
distinct economic growth patterns across the four SRES scenario families, as
summarized in Tables 4-5, 4-6, and 4-7. The scenarios of rapid development and
"catch-up" remain in dispute within the SRES writing team because they imply
high productivity growth (see Box 4-5 and, for a
contrasting viewpoint and scenario interpretation, Box
4-6). However, it is agreed that such scenarios of high productivity growth
and smaller income-per-capita disparities cannot be ruled out, even if they
certainly are very challenging from the perspective of recent growth experiences
in a number of regions, most notably Africa. There is also agreement that the
assumptions deployed for the SRES scenarios are within the range suggested by
the literature (see Chapter 2). In this the highest GDP
growth is up to US$700 trillion by 2100 compared to US$550 trillion in the highest
SRES scenario. For scenarios developed within the context of sustainability
analyses, reductions in per capita income gaps also occur faster than for any
of the scenarios presented here.

Table 4-5: Historical economic
growth rates (% per annum) from 1950 (Maddison, 1989, 1995; UN, 1993a, 1993b),
and SRES scenarios for 1990 to 2100. Growth rates were calculated on the
basis of GDP at 1990 prices and market exchange ratesa . Long-term
growth rates are lower than those from 1950 to 1990 (e.g., the average annual
growth rate for OECD90 countries from 1850 to 1990 was about 2.8%, and for
the reforming economies in Eastern Europe and the Former Soviet Union it
was about 1%; Maddison, 1989). Numbers in brackets give the minimum and
maximum values of all SRES scenarios.

Economic Growth Rates (% per annum)

1990-2050

1990-2100

Region

1950-1990

A1

A2

B1

B2

A1

A2

B1

B2

OECD90

3.9

2.0
(1.2-2.2)

1.6
(1.0-2.1)

1.8
(1.7-2.0)

1.4
(1.3-1.6)

1.8
(0.9-1.9)

1.6
(0.9-1.7)

1.5
(1.4-1.5)

1.1
(1.0-1.3)

REF

4.8

4.1
( 2.8-4.6)

2.3
(0.6-2.3)

3.1
(2.7-3.7)

3.0
(1.9-3.3)

3.1
(2.2-3.5)

2.5
(1.6-2.5)

2.7
(2.4-2.7)

2.3
(1.6-2.5)

IND

3.9

2.2
(1.4-2.4)

1.6
(1.0-2.1)

1.9
(1.8-2.0)

1.6
(1.4-1.8)

2.0
(1.1-2.1)

1.7
(1.0-1.7)

1.6
(1.5-1.6)

1.3
(1.1-1.4)

ASIA

6.4

6.2
(5.8-6.6)

3.9
(3.8-4.8)

5.5
(5.3-6.2)

5.5
(4.2-5.7)

4.5
(4.2-4.7)

3.3
(3.3-3.7)

3.9
(3.8-4.2)

3.8
(3.6-3.9)

ALM

4.0

5.5
(4.8-5.8)

3.8
(3.3-4.1)

5.0
(4.5-5.3)

4.1
(3.3-4.4)

4.1
(3.9-4.2)

3.2
(3.1-3.4)

3.7
(3.5-3.9)

3.2
(3.0-3.6)

DEV

4.8

5.9
(5.3-6.2)

3.8
(3.5-4.4)

5.2
(4.9-5.7)

4.9
(3.7-5.0)

4.3
(4.1-4.4)

3.3
(3.3-3.6)

3.8
(3.7-4.1)

3.5
(3.3-3.7)

WORLD

4.0

3.6
(2.9-3.7)

2.3
(1.7-2.8)

3.1
(2.9-3.5)

2.8
(2.1-2.9)

2.9
(2.5-3.0)

2.3
(2.0-2.3)

2.5
(2.5-2.6)

2.2
(2.0-2.3)

Note: independent rounding.

A. In the calculations the concept of logarithmic growth rates is used.

Table 4-6: Income
per capita (1000 US dollars at 1990 prices and exchange rates) in the world
and by SRES region. Numbers in brackets give minimum and maximum values
of the SRES scenarios. The range for 1990 illustrates differences in base-year
calibration across models.

Income per Capita by World and Regions (103
1990US$ per capita)

2050

2100

Region

1990

A1

A2

B1

B2

A1

A2

B1

B2

OECD90

17.8-20.6

50.1
(39.4-62.3)

34.6
(32.3-54.0)

49.8
(40.3 -52.0)

39.2
(35.1-42.2)

109.2
(69.8-115.7)

58.5
(48.0-78.7)

79.7
(70.6-84.7)

61.0
(50.1-73.2)

REF

2.2-2.7

29.3
(13.5-32.5)

7.1
(3.3-9.0)

14.3
(12.4-23.4)

16.3
(7.8-16.8)

100.9
(39.9-119.3)

20.2
(13.5-20.2)

52.2
(41.2-56.4)

38.3
(14.0-38.3)

IND

12.8-14.4

44.2
(30.7-50.0)

26.1
(22.4-41.9)

39.1
(32.5-40.8)

32.5
(27.0-34.7)

107.3
(60.3-113.5)

46.2
(37.1-64.5)

72.8
(65.3-77.7)

54.4
(42.4-61.1)

ASIA

0.4-0.6

14.9
(10.8-15.7)

2.6
(2.5-4.5)

9.0
(7.2-14.3)

8.9
(3.6-9.5)

71.9
(38.8-76.8)

7.8
(7.4-12.9)

35.7
(35.7-46.1)

19.5
(14.8-20.6)

ALM

1.3-2.1

17.5
(12.2-18.0)

6.0
(4.2-6.0)

13.6
(8.0-15.3)

6.9
(4.4-7.7)

60.9
(44.2-69.5)

15.2
(11.3-15.2)

44.9
(41.3-45.8)

16.1
(13.6-22.6)

DEV

0.7-1.1

15.9
(11.4-16.7)

3.9
(3.3-5.1)

10.9
(7.5-14.8)

8.1
(3.9-8.4)

66.5
(41.4-69.8)

11.0
(10.3-13.7)

40.2
(40.2-45.2)

18.0
(14.2-21.5)

WORLD

3.7-4.0

20.8
(14.3-21.5)

7.2
(6.0-9.9)

15.6
(12.7-19.1)

11.7
(7.7-11.9)

74.9
(43.7-77.9)

16.1
(15.9-16.9)

46.6
(46.3-49.6)

22.6
(19.2-24.5)

Table 4-7: Growth
rates (% per year) of income per capita (using GDP at 1990 prices and exchange
rates) in the world and by region. Historical data from 1950 to 1990 from
Maddison (1989, 1995), UN (1993a, 1993b), and Klein Goldewijk and Battjes
(1995). Numbers in brackets give minimum and maximum values of all SRES
scenarios.

Growth Rates of Income Per Capita (%)

1990-2050

1990-2100

Region

1950-1990

A1

A2

B1

B2

A1

A2

B1

B2

OECD90

2.8

1.6
(1.2-1.8)

1.1
(0.8-1.6)

1.5
(1.2-1.6)

1.2
(1.0-1.4)

1.6
(1.2-1.7)

1.1
(0.8-1.2)

1.2
(1.2-1.3)

1.1
(0.9-1.3)

REF

3.7

4.0
(2.8-4.5)

1.9
(0.5-2.2)

3.0
(2.7-3.6)

3.0
(1.9-3.3)

3.3
(2.5-3.4)

2.0
(1.5-2.0)

2.8
(2.6-2.8)

2.4
(1.6-2.6)

IND

2.9

2.0
(1.3-2.1))

1.2
(0.8-1.8)

1.7
(1.5-1.8)

1.4
(1.1-1.6)

1.9
(1.3-2.0)

1.2
(0.9-1.4)

1.5
(1.4-1.5)

1.2
(1.0-1.4)

ASIA

4.4

5.5
(5.1-5.9)

2.7
(2.7-3.6)

4.8
(4.6-5.5)

4.7
(3.3-4.8)

4.4
(3.9-4.7)

2.5
(2.4-2.9)

3.9
(3.8-4.2)

3.3
(3.1-3.4)

ALM

1.6

4.0
(3.5-4.4)

1.9
(1.7-2.2)

3.5
(3.1-3.9)

2.4
(1.7-2.7)

3.3
(3.1-3.5)

1.9
(1.8-2.1)

3.0
(2.8-3.2)

2.1
(1.9-2.5)

DEV

2.7

4.9
(4.4-5.2)

2.4
(2.3-3.0)

4.2
(3.9-4.8)

3.8
(2.5-3.9)

4.0
(3.6-4.1)

2.2
(2.2-2.6)

3.5
(3.4-3.7)

2.8
(2.6-3.0)

WORLD

2.2

2.8
(2.2-2.9)

1.1
(0.7-1.5)

2.3
(2.1-2.6)

1.8
(1.1-1.9)

2.7
(2.2-2.8)

1.3
(1.3-1.5)

2.2
(2.2-2.4)

1.6
(1.4-1.7)

Important differences remain between models in terms of 1990 base-year data
on economic activity levels. Even after differences in regional definitions
are accounted for, 1990 regional GDP differences between models range up to
±32% in a few cases. Such differences are particularly pronounced for developing
countries, where in many cases national currencies are not freely convertible
and thus important uncertainties on the applicable conversion rates remain (World
Bank, 1999). Differences for OECD countries are much smaller (±3% across the
models) and because of their current dominance in global economic activity (and
counterbalancing effects), 1990 global GDP numbers agree well across the models
(±5%). Scenario comparisons, especially at the regional level, are therefore
best based on a comparison of growth rates (see Chapter 2),
and the SRES scenarios are no exception.

Historical data indicate that, even though the process of economic growth is
heterogeneous across countries and over time, the patterns of growth show certain
similarities. Economic "catch-up" follows a general dynamic pattern, characterized
by initially accelerating economic growth rates that pass through a maximum,
and decline once the industrial base of an economy becomes established. This
overall feature of growth dynamics is reflected in all the SRES scenarios, albeit
timing and magnitude vary across the four scenario families. This variation
reflects the scenario-specific storylines, as well as particular relationships
to other driving-force variables, such as demographics, described in the scenario.